Creating a tool to scan and diagnose moles.

The Challenge

The average person has around 30-40 moles; some have as many as 600. Most moles are completely harmless, but there are some that could be dangerous — and, while there are signs to look for, it's very difficult to self-diagnose. To determine whether a mole is dangerous or not, you need to go see a dermatologist — and the wait time to get an appointment with a dermatologist can be long. What if there were a way for people to get their suspicious moles diagnosed without needing to go to a dermatologist's office?

Enter: SiaCloud. Our client created a scanner that takes pictures of the layers of skin under a mole. Using these pictures, a dermatologist can very accurately diagnose the mole — much more accurately than using a photo from a regular camera.

They were using the tool with an old, PC-based software program. This program had to be installed on each local machine that would be using the scanner (think of the CD-ROM days). All files were stored on the local machine, so sending files to dermatologists was very manual and working on multiple machines was not possible.

The tool's user experience was also not optimal: everyone (dermatologists, scanning technicians) used the same tool. They were provided with a feature-heavy dashboard that had no clear path through it. It required a lot of training. Dermatologists and technicians are busy people, and we needed to maximize how many patients they could see. They needed the tool to be optimized for their own uses.

The Process

We started the project with a kick-off meeting, where the client demoed the current tool for us. We then did a business needs workshop, where we helped the client outline the issues that they needed to address with the current system, to identify KPIs, and to define their business model going forward.

The next step was creating personas. Again, we did a workshop with the client where we identifed the main users. We went off and did some research of our own to flush these out, and ended up with a user hierarchy tree and proto-personas outlining the challenges and needs of each user type.

SiaCloud User Hierarchy

We used these personas to define the tasks that each user would need to do, and then outlined the steps they would need to perform to complete each task. Here's one of the final user flows:

SiaCloud User Flow

While doing the user flows, we did some rough sketches to help make sense of the tasks. These were turned into interactive wireframes.

SiaCloud Sketches

At this stage, we wanted to test the system with our two primary user groups: dermatologists and scanning technicians. We created a prototype and proceeded to test it with real users. Our observations helped us streamline each user's path through the tool.

SiaCloud Prototype

Now that our wireframes had been tested, we started with UI designs. These were kept simple and clean so as not to distract users from the task at hand.

SiaCloud UI Design
SiaCloud UI Design
SiaCloud UI Design
SiaCloud UI Design

A design system was created and outlined in a style guide to ensure consistency.

SiaCloud Style Guide

The Solution

We created a cloud-based solution so that users would be able to login anywhere and access the same patient records — depending on their location and permissions. Based on the user's account type, they access a different part of the tool — scanning technicians get the tool to add patient records and scan moles, dermatologists get the tool to review and diagnose moles, and everyone else gets reporting and user account management tools. Each user's experience is streamlined to allow them to complete their individual tasks as quickly and easily as possible, with very minimal training. We also introduced a more modern look to the software.

The client is very happy with the final solution, and is currently planning to roll it out in a few different countries.


Workshop facilitation, persona creation, user flows, wireframes, prototyping, user testing, UI designs, design system creation


Blanc Labs

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